ID 原文 译文
39296 本文首先进行的理论研究结果表明周期性视觉刺激光源面积变化和SSVEP性能变化密切相关;然后侧重实验研究不同LED光源刺激面积变化对SSVEP共振频率的影响规律: In this article, the theoretical research results showed that the change of the area of periodic visual stimulation light source was closely related to the change of SSVEP, and the influence of the stimulation area of different LED sources on SSVEP resonance frequency was studied experimentally.
39297 首先采集不同光源面积刺激下的SSVEP信号，对其依次进行50 Hz陷波、带通滤波(带宽为3～35 Hz)去噪、去趋势与眼电等预处理; First, SSVEP signals under the stimulus of different light sources were collected and preprocessed by 50 Hz notch, band-pass filter(bandwidth 3～35 Hz) de-noising, de-trending and de-eye-electricity.
39298 然后基于快速傅里叶变换进行频谱分析，计算不同刺激频率下的SSVEP平均归一化基波功率，以确定SSVEP的共振频率。 Then, the average normalized fundamental power of SSVEP under different stimulation frequencies was calculated based on the spectrum analysis of FFT to determine the SSVEP resonance frequency.
39299 结果表明:当光源半径和刺激频率分别在5～9 mm和6～20 Hz取值时，SSVEP共振频率随光源面积变化的规律是:当光源面积小于某阈值时，共振频率与光源面积正相关; The results showed that when the light source radius was 5～9 mm and the stimulation frequency was 6～20 Hz, the law of SSVEP resonance frequency changing with the light source area was that when the light source area was less than a certain threshold, the resonance frequency was positively correlated with the light source area. when the threshold was exceeded, the resonance frequency was negatively correlated with the light source area.
39300 而超出这个阈值时，共振频率与光源面积负相关。此外本文用闪光LED作为刺激源，可有效解决以屏幕闪光为刺激源时存在的频率选择受限于屏幕刷新率的问题。 In addition, this article used flash LED as stimulation source, which could effectively solve the problem that the frequency selection was limited by the screen refresh rate when screen flash was used as stimulation source.
39301 本文研究结果可为神经系统疾病的预测或诊断和SSVEP在脑机接口领域的有效应用提供有意义的理论和实验依据。 The results of this study can provide significant theoretical and experimental basis for the prediction or diagnosis of nervous system diseases and the application of SSVEP in BCI.
39302 考虑到零水印算法的优越性以及目前针对3D高效视频编码标准的视频水印算法少的情况，提出了一种抗重压缩编码的视频零水印算法。 Considering the advantages of the zero-watermarking algorithm and the shortage of the video watermarking for 3-dimentional high efficiency video coding. A video zero-watermarking algorithm is proposed.
39303 首先，利用I帧的深度图及非I帧的运动矢量和编码单元划分情况对水印的构造位置进行选择。 Firstly, the depth map of I frame and the motion vectors and coding unit partitions of non-I frame are used to select the position for watermark construction.
39304 其次，通过全相位双正交变换及奇异值分解对16×16块进行处理，获取最大奇异值的最高有效位作为最终的特征信息。 Secondly, apply all phase biorthogonal transform and singular value decomposition to 16 × 16 blocks to obtain the most significant bit of the maximum singular value, and define the most significant bit as the final characteristic information.
39305 最后，得到的特征信息与图像水印进行异或生成零水印并进行零水印注册。 Finally, the XOR operation between the characteristic information and image watermark is performed to generate the zero watermark for registration.